Simulation techniques are available which enable an ability to forecast and analyze potential future events. For example, in business realms, simulation tools exist which enable business owners to forecast an effect of potential increases or decreases in sales, production capacity, and other business metrics which may vary over time. Similarly, in financial realms, simulation tools enable an ability to test assumptions about possible outcomes in equities markets. In yet another example, simulations may help to estimate the consequences of changing the setup of an existing supply chain, for instance, by changing the available production or transportation capacities, safety stocks, the number of distribution centers or other important components.
In general, such simulation tools may perform operations on a data set which includes factual or expected data representing a current or possible state of relevant factors and variables, to thereby generate expected values and outcomes for such data variables. In this way, simulations may be created which represent changes over time and/or a final outcome at a selected future time, so that a user of the simulation tools may consider such information when deciding how to proceed. For example, in the examples given above, users of appropriate simulation tools may discover that the simulation tools predict that, e.g., opening a new production facility will increase profits.
In many simulation scenarios, the data on which the simulations are to be based may be relatively small in amount, and/or may be relatively static over a relevant period of time. In many other simulation scenarios, however, it may occur that the data on which the simulations will be based is very large in size, and/or may vary in time during a relevant time period during which the simulations are to be executed. In the latter case(s), the requirement to use a very large amount of data to produce (e.g., to copy the data from a given source, in parts or completely) the simulation may require a producer or consumer of the simulation to wait an undesirably inconveniently long time for the simulation to be produced. Moreover, due to factors such as, e.g., changes in the underlying data set which may occur during execution of two or more related simulations, it may be difficult or impossible to obtain meaningful comparisons between the two or more simulations, particularly in cases where simulations are often maintained and/or used for many days or weeks, while related business data may change significantly each day. Thus, for these and other reasons, it may be difficult for simulation users to obtain satisfactory results within an acceptable timeframe.